KR101335944B1 - Method for Extracting Optimal Infra Data, Apparatus and Computer-Readable Recording Medium with Program Therefor - Google Patents

Abstract

The optimal infrastructure data extraction method, the apparatus and the computer-readable recording medium according to the embodiment of the present invention set the number of batteries used and the number of cable installation section installed in the driving route; Generate a population of a predetermined number of individuals; Calculate infrastructure construction costs for each entity; Extracting the best object having the lowest value among the infrastructure construction costs of all the objects; Extracting self-optimal positions for each individual; Outputting and terminating the best object when a termination condition is satisfied for the population; Set an arbitrary movement speed for each individual; Each object is characterized by moving the position of the object according to the vector toward the best object, the vector representing the self-optimal position and the speed.

Description

Method for Extracting Optimal Infra Data, Apparatus and Computer-Readable Recording Medium with Program Therefor}

Embodiments of the present invention relate to a method of extracting optimal infrastructure data, an apparatus therefor and a computer-readable recording medium. More specifically, the optimal infrastructure data extraction method for optimally determining the battery capacity and the feeding section of the power supply cable of the moving object that is charged with electricity during the movement, and the device and the computer-readable recording medium therefor It is about.

The contents described in the following sections provide background information related to the embodiments of the present invention, but it does not constitute a prior art.

On-line electric vehicles (hereinafter referred to as OLEVs), unlike conventional electric vehicles, are a new concept of electric vehicles that are powered by a wireless method from a cable buried in a road while driving and stopping.

When the OLEV is driving a cable-embedded section, it is supplied with electricity by a wireless method to deliver electricity to the motor, and the remaining electricity is sent to the battery to charge the battery. Like ordinary electric cars, OLEVs operate by supplying electricity from batteries.

For wireless charging / charging, an inverter that generates electricity and a cable that delivers it must be buried on the road. One inverter is installed together in one independent cable buried section, and the OLEV is wirelessly supplied with the cable electricity through a pickup device installed at the bottom.

Generally, the battery is a high cost item so that the battery price accounts for more than 40% of the price of the electric vehicle. The more the battery is installed in the electric vehicle, the higher the battery cost, and the greater the weight of the vehicle. It also consumes more.

Electric vehicle systems are largely always powered from a cable by means of contact (eg, trains, streetcars) and when powered from their own battery without charging / charging while driving (b, eg, general electricity). Car), and can be divided into two.

In the case where the electricity is always supplied from the cable in a contact manner (a), the battery capacity and cost need not be considered because the battery is not installed. Since cables must be installed in all sections of the road, no consideration is needed. However, there are aesthetic and environmental problems caused by many cable constructions.

(B) If the battery is supplied from its own battery without charging / charging while driving, the battery capacity should be taken into account, but this is often determined by the use of the vehicle rather than the cost side, and directly affects the selling price of the electric vehicle. For example, for short-distance driving in factories, golf courses, etc .: small battery capacity, city-type electric vehicles running only in cities: medium battery capacity, electric vehicles for general automotive use: large battery capacity). Therefore, in this case, cable construction and battery capacity determination in terms of cost are not a big consideration.

In the case of OLEV, a new concept electric vehicle, it is possible to have two types of trade-offs, which can take advantage of two types of eco-friendly electric vehicle operation system with minimum cost and many advantages. In order to maximize cost minimization, it is necessary to determine the optimal battery capacity and the charging / discharging section of the charging cable, unlike the above two types.

An embodiment of the present invention has an object of optimally determining the battery capacity and the embedding section of the feeder cable of the moving object to charge the electricity while moving the predetermined section.

In order to achieve the above object, an embodiment of the present invention, the target setting unit for setting the number of battery installation and the number of cable installation section is installed in the driving path; An entity generation unit generating an entity set consisting of a predetermined number of entities; A cost calculator for calculating an infrastructure construction cost for each entity; Best object extraction unit for extracting the best object having the minimum value among the infrastructure construction cost of all the objects; A self optimum position extracting unit for extracting a self optimum position for each individual entity; A condition determination unit for outputting and terminating the best object when a termination condition is satisfied for the population; A speed setting unit for setting an arbitrary moving speed for each individual object; And a position moving unit for moving the position of the object according to the vector, the vector toward the best object, the vector representing the self optimal position, and the speed for each individual object.

In the object generating unit, the object may be set by using the capacity of the battery, the position of the start point and end point for each cable installation section as a variable.

In the individual generation unit, the individual,

The range of each variable can be set to any value within that range.

Each variable of the entity may be set randomly within a range of valid values.

The movement speed for each individual entity may be determined according to the difference between the position of the best object and the current position.

The condition determination unit may end when the number of times of calculating the infrastructure construction cost becomes a predetermined number.

In the object generating unit, the position of the start point for each cable installation section may be set to be smaller than the position of the end point.

In the object generating unit, the object may be set so as not to overlap with the other cable installation section between the position of the start point and the end point of any one of the cable installation section.

At the position indicating the first starting point, which is the starting point of the first cable installation section, the size of the first starting point is subtracted so that the magnitude of the battery's maximum chargeable power minus the power consumption to the first starting point is within a range larger than the recommended minimum charge amount of the battery. You can set the location.

The amount of power at the first end point, which is the end point of the first cable installation section, is the maximum charge possible as the sum of the amount of charge at the first cable installation section minus the power consumption to the first end point from the maximum chargeable power of the battery. It can be implemented not to be greater than the amount of power.

The starting point of the next cable installation section may be set such that the amount of power consumed from the end point of any one cable installation section minus the power consumption to the start point of the next cable installation section is within a range larger than the minimum charge recommendation amount of the battery.

The amount of power available at the next end point, which is the end point of the next cable installation section, is the magnitude of the maximum chargeable power as the sum of the power consumption of the end point of the previous cable installation section and the amount of charge at the next cable installation section. It can be implemented not to be larger.

The amount of power at the end point of the running route is the size of the end point of the last cable installation section minus the power consumption from the end point of the last cable installation section to the end of the last cable installation section. Can be set.

Another embodiment of the present invention to achieve the above object, the object setting step of setting the number of the battery installation and the number of cable installation section is installed in the driving path; An entity generation step of generating an entity set consisting of a predetermined number of entities; A cost calculation step of calculating an infrastructure construction cost for each individual; Best object extraction step of extracting the best object having the minimum value among the infrastructure construction cost of all the objects; A self optimum position extraction step of extracting a self optimum position for each individual; A condition determination step of outputting and ending the best object when the termination condition is satisfied for the population; A speed setting step of setting an arbitrary moving speed for each individual; And a position shifting step of moving the position of the object according to the vector, the vector indicating the best object, the vector indicating the optimal position, and the speed for each individual object.

In the individual generation step, the individual may be set by using the capacity of the battery, the position of the start point and end point for each cable installation section as a variable.

In the individual generation step, the position of the start point for each cable installation section may be set to be smaller than the position of the end point.

In the individual creation step, the individual may be set so as not to overlap with the other cable installation section between the position of the start point and the end point of any one of the cable installation section.

The entity representing the start point of a certain cable installation section may be set such that the size obtained by subtracting the power consumption amount up to the cable installation section before the start point is larger than the recommended minimum charge amount of the battery.

The amount of power at the end point of the running route is the size of the end point of the last cable installation section minus the power consumption from the end point of the last cable installation section to the end of the last cable installation section. Can be set.

In order to achieve the above object, another embodiment of the present invention provides a computer readable recording medium having recorded thereon a program for executing each step of the optimal infrastructure data extraction method.

According to an embodiment of the present invention, there is an effect of optimally determining the battery capacity and the embedding section of the feed cable of the mobile body which is charged with electricity during the movement of a predetermined section. Therefore, it is possible to construct an optimal OLEV operation system with minimum investment cost.

1 is a conceptual diagram illustrating a case where an OLEV equipped with a battery charges while driving a section in which a power feeding cable is installed.
2 is a block diagram illustrating an apparatus for extracting optimal infrastructure data according to an embodiment of the present invention.
3 is a flowchart illustrating a method of extracting optimal infrastructure data according to an embodiment of the present invention.

Hereinafter, some embodiments of the present invention will be described in detail with reference to exemplary drawings. It should be noted that, in adding reference numerals to the constituent elements of the drawings, the same constituent elements are denoted by the same reference symbols as possible even if they are shown in different drawings. In the following description of the present invention, a detailed description of known functions and configurations incorporated herein will be omitted when it may make the subject matter of the present invention rather unclear.

In addition, in describing the component of this invention, terms, such as 1st, 2nd, A, B, (a), (b), can be used. These terms are intended to distinguish the constituent elements from other constituent elements, and the terms do not limit the nature, order or order of the constituent elements. When a component is described as being "connected", "coupled", or "connected" to another component, the component may be directly connected to or connected to the other component, It should be understood that an element may be "connected," "coupled," or "connected."

1 is a conceptual diagram illustrating a case where an OLEV equipped with a battery charges while driving a section in which a power feeding cable is installed.

As shown in FIG. 1, an OLEV 100 equipped with a battery 110 having a capacity of Imax is supplied with electric power from a power feeding cable 120 installed below a road while traveling on a road. Here, each feed cable 120 receives power from each inverter 130.

Here, the relationship between the battery capacity of the OLEV and the buried section of the charging / feeding cable has a trade-off relationship. That is, when the capacity of the battery 100 is increased, since the OLEV 100 can be driven at a greater distance by its own electric energy, the embedding section and length of the cable 120 requiring charging / feeding during the operation may be reduced. However, when the buried section and the length of the charging / feeding cable 120 is increased, the charging / feeding can be more during operation, the capacity of the battery 110 to be mounted on the OLEV 100 can be reduced.

In general, the installation of the charging / feeding cable 120 takes about 500 million won per km, and the battery 110 installed in the OLEV bus, depending on the capacity, but the cost of more than 100 million won per unit. Therefore, before actually building the system in which OLEV is operated, the optimal capacity of 1) battery capacity and 2) charging / feeding cable can be minimized in consideration of the cost of battery 110 and charging / feeding cable 120. If the buried section is decided, the optimal OLEV operation system can be constructed with minimum investment cost.

2 is a block diagram illustrating an apparatus for extracting optimal infrastructure data according to an embodiment of the present invention.

As shown in FIG. 1, the optimal infrastructure data extraction apparatus 200 according to an embodiment of the present invention includes a target setting unit 210, an object generation unit 220, a cost calculation unit 230, and a best object extraction unit ( 240, the condition determination unit 250, the self-optimal position extraction unit 260, the speed setting unit 270, and the position moving unit 280 may be configured.

The apparatus 200 for extracting optimal infrastructure data according to an embodiment of the present invention may extract optimal infrastructure data using a particle swarm optimization (PSO) algorithm.

The target setting unit 210 sets the number of batteries used and the number of cable installation sections installed in the driving path. That is, the number of running of the electric vehicle (OLEV) equipped with a battery having a predetermined capacity and the number of cable installation sections (that is, the number of installation of the feed cable in FIG. 1) are set.

The entity generation unit 220 generates an entity set composed of a predetermined number of entities. When the number of batteries used by the target setting unit 210 and the number of cable installation sections installed in the driving path are set, the generated object is set by using the capacity of the battery, the starting point and the end point location for each cable installation section as variables. do. Therefore, if the number of cable installation sections is 10 (battery capacity, start position of the first installation section, position of the end point of the first installation section, start position of the second installation section, position of the end point of the second installation section,. .., the starting position of the tenth installation section and the position of the end point of the tenth installation section).

Here, each object is determined randomly by setting a range of each variable to any value within the set range. In addition, each variable of the object is set randomly within the range of valid values.

Valid ranges of values are as follows:

1. For each cable installation section, the position of the starting point (x _i ^o ) is set to be smaller than the position of the end point (x _i ^f ). That is, Equation 1 is satisfied.

Further, the object is set so as not to overlap with the other cable installation section between the position of the start point and the end point of any one cable installation section. Therefore, as shown in Equation 2, the position of the start point of any one cable installation section is set to be larger than the position of the end point of the previous cable installation section.

Further, at the position (x _1, ^o) of the first starting point is the starting point of the first cable installation section, of the size at the maximum chargeable electric energy of the battery (I _high) from the starting point of the operation path obtained by subtracting the power consumption to the first starting point battery The position of the first starting point is set to be within a range larger than the minimum charge recommendation amount I _low , which satisfies Equation 3.

The maximum chargeable power amount I _high of the battery is generally multiplied by a predetermined ratio α by the maximum capacity I max of the battery, and is usually 0.8 to 0.9.

In addition, the power consumption amount up to the first starting point has a value integrating the required power per time P _bat (t) in the corresponding section with respect to time, and assuming that the OLEV moves at a constant speed, ₁ ^o ) (i = 1 in equation 3).

In addition, the amount of power at the first end point (x ₁ ^f ), which is the end point of the first cable installation section, is obtained by subtracting the power consumption from the start point of the driving route to the first end point at the maximum chargeable power amount I _high of the battery. The amount of charge in the cable installation section (I _CS (t ₁ ^f -t ₁ ^o )) should be added, but not greater than the maximum chargeable power. This is shown in Equation 4.

In Equation 4, i = 1.

Here, subtract the power consumption from the end point (x _i ^f ) of one cable installation section to the start point (x _{i +1} ^o ) of the next cable installation section so that the size is within the range larger than the recommended minimum charge of the battery. The starting point (x _{i +1} ^o ) of the cable installation section is set. This is shown in Equation 5.

In Equation 5, the power consumption from the i th end point to the (i + 1) th start point is the integral of the required power per hour P _bat (t) with respect to time in the interval, and the OLEV moves at a constant speed. If it is assumed, the time t _i ^f of the i th end point and the time t _{i +1} ^o at the (i + 1) th start point can be obtained for the length of the corresponding interval.

And, the following end points the end points of the cable installation interval (x _{i +1} ^f) the amount of power, the end points of the cable section installed in the power of the end points of the cable prior to installation interval (x _i ^f) at (x _{i +1} ^f) Subtract the power consumption up to and add the charge amount (I _CS (t _{i +1} ^f -t _{i +1} ^o )) in the next cable installation section, so as not to be greater than the maximum chargeable power (I _high ). This is shown in Equation 6.

In Equation 6, the power consumption from the i th end point to the (i + 1) end point is the integral of the required power per hour P _bat (t) with respect to time in the interval, and the OLEV moves at a constant speed. If it is assumed, the time t _i ^f of the i th end point and the time t _{i +1} ^f at the (i + 1) th end point can be obtained for the length of the corresponding interval.

In addition, the amount of power at the end of the operation path, the final cable installation to be greater than the minimum charge RDA (I _low) as the size obtained by subtracting the power consumption up to the end point (T) of the driving route from the amount of power of the end point of the last cable installation interval The position of the end point t _n ^f of the section is set. This is shown in equation (7).

In Equation 7, the power consumption from the end point of the last cable installation section to the end point of the driving route has an integral value of the required power per hour (P _bat (t)) in the corresponding section over time. Assuming the movement, the time (t _n ^f ) of the end of the last cable installation section and the time (T) of the end of the route can be obtained for the length of the section.

The cost calculator 230 calculates an infrastructure construction cost for each entity. Here, the cost may be calculated as shown in Equation 8.

In Equation 8, p (Imax) is the cost for k batteries having a capacity of Imax, and c (x _i ^f -x _i ^o ) is the cost for the i th cable installation section. The cost for the i-th cable run includes not only the cable cost, but also the cost of the inverter for that run. k means the total number of vehicles driving the driving route.

The best object extractor 240 extracts a best object having a minimum value among infrastructure construction costs of all objects.

The best object extractor 240 calculates an infrastructure construction cost according to Equation 8 for each individual. Here we find the entity representing the minimum cost.

The condition determination unit 250 outputs the best object and ends when the termination condition is satisfied for the population. Here, the termination condition may be terminated when the number of times the position shift is performed while performing the PSO algorithm is a predetermined number. In this case, an end condition such as the number of position movements may be set at the stage in which the target setting unit 210 performs the target setting step.

The self optimum position extractor 260 extracts a self optimum position for each individual entity. That is, the self-optimal position extraction unit 250 has a position representing the best infrastructure construction cost among the positions that have moved to each individual including the current point, and sets it as its optimal position.

Other termination conditions may be set to terminate according to the distance between the entities. Here, the distance between the objects may be set to terminate when the sum of the distances between the objects is less than or equal to the preset distance, but the termination condition may be set by other various methods.

The speed setting unit 270 sets an arbitrary moving speed for each object. Each object can be set to have an arbitrary speed, and the minimum and maximum values of the speeds that can be set can be set before the objects move for the first time, and after the objects move, depending on the distance between the objects. Alternatively, the speed minimum and maximum values may be set in various other ways to set a speed having a random magnitude between the given minimum and maximum values. These speeds can be set differently for each object. Also, the direction in which the speed is directed may be set randomly. In this way, a vector represented by a randomly set speed for each individual can be obtained.

When the speed setting unit 270 moves the position of the object according to the vector toward the best object, the vector representing the self-optimal position, and the vector representing the speed for each object, the speed setting unit 270 selects the object for each object with respect to the position where the movement is expected. If the constituent variables satisfy the equations (1) to (8) and are valid, and if the variables are not valid, the generation of the vector indicating the velocity for the object may be canceled and the velocity vector may be randomly generated. Also, in this case, the velocity vector can be set as a zero vector, and even after the velocity vector is set to zero, the object's constituent variables can be moved at the position where the object is expected to move by using the vector toward the best object and the vector representing its optimal position. If they do not satisfy the equations (1) to (8), the coefficients of a, b, and c used to calculate the movement position by using Equation 9 to be described later may be set to 0 so that the movement does not occur with respect to the object. . In addition, in order to limit the movement to the area within which the object can move, a random speed within a range in which the moving position determined by the vector toward the best object, the vector representing its optimal position, and the vector representing the velocity becomes a valid position. Vectors can be generated. The method of generating the velocity vector for determining the moving position as described above may be set in various ways.

The position moving unit 280 moves the position of the object according to the vector toward the best object, the vector representing its optimal position, and the vector representing the velocity for each individual.

In this case, the moving position may be determined by multiplying a vector directed toward a best object, a vector representing a self-optimal position, and a vector representing a velocity by an individual proportional constant, and then adding them all together to determine the position where the object moves. This is shown in Equation 9 below.

[Equation 9]

Move position = current position + [a * (vector toward the best object) + b * (vector representing his best position) + c * (vector representing velocity)]

Herein, the proportional constants a, b, and c may be randomly set within an arbitrary range, and the range may be determined differently according to the current state of the entity, such as the position of the entity. For example, the value may be set in such a manner that the ranges of a, b, and c become smaller when the best object is close, and the range of a, b, c becomes larger when the best object is far away.

3 is a flowchart illustrating a method of extracting optimal infrastructure data according to an embodiment of the present invention.

Optimal infrastructure data extraction method according to an embodiment of the present invention is a target setting step (S310) for setting the number of the battery used and the number of cable installation section installed in the driving path, generating a set of objects consisting of a predetermined number of objects The object generation step (S320), the cost calculation step (S330) for calculating the infrastructure construction costs for each individual, the best object extraction step (S340) for extracting the best object having the minimum value among the infrastructure construction costs of all the objects, Condition determination step (S350) for determining whether the end condition is satisfied for the object set, self-optimal position extraction step (S360) for extracting the self-optimal position for each individual, if the termination condition is not satisfied, random for each individual According to the speed setting step (S370) of setting the moving speed of the object and the vector toward the best object for each object, the vector and the speed indicating its optimum position. Position moving step (S380) of moving the position of the object, if they meet the termination condition in step S350 and a step (S390) for outputting the best objects and exit. The order shown here is only an example and may be implemented by changing the order of each step depending on the embodiment.

Here, the target setting step S310 corresponds to the operation of the target setting unit 210, and further, the object generation step S320, the cost calculation step S330, and the best object extraction step S340 are each an object generation unit 220. ), Corresponding to the operations of the cost calculation unit 230 and the best object extraction unit 240 will be omitted.

The condition determination step S350 corresponds to the operation of the condition determination unit 250. If the end condition is satisfied as a result of the determination in the condition determination step S350, the process proceeds to the step of outputting and ending the best object (S390). do.

If the determination result in the condition determination step (S350) does not satisfy the end condition, the self-optimal position extraction step (S360), the speed setting step (S370), and the position moving step (S380) extracting the self-optimal position for each individual object. Proceed to the cost calculation step (S330) through.

As described above, the optimum infrastructure data can be extracted by extracting the best object at the end of the loop after repeating the loop until the end condition is satisfied.

As described above, the method for extracting optimal infrastructure data according to an embodiment of the present invention described in FIG. 3 may be implemented in a program and recorded in a computer-readable recording medium. A computer-readable recording medium having recorded thereon a program for implementing an optimal infrastructure data extraction method according to an embodiment of the present invention includes all kinds of recording devices that store data that can be read by a computer system. Examples of such computer-readable recording media include ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage, etc., and also implemented in the form of a carrier wave (e.g., transmission over the Internet) . The computer readable recording medium may also be distributed over a networked computer system so that computer readable code is stored and executed in a distributed manner. In addition, functional programs, code, and code segments for implementing an embodiment of the present invention may be easily inferred by programmers skilled in the art to which an embodiment of the present invention belongs.

The foregoing description is merely illustrative of the technical idea of the present invention, and various changes and modifications may be made by those skilled in the art without departing from the essential characteristics of the present invention. Therefore, the embodiments disclosed in the present invention are intended to illustrate rather than limit the scope of the present invention, and the scope of the technical idea of the present invention is not limited by these embodiments. The protection scope of the present invention should be interpreted by the following claims, and all technical ideas within the equivalent scope should be interpreted as being included in the scope of the present invention.

As described above, the present invention has the effect of optimally determining the battery capacity and the buried section of the feed cable of the mobile body which is charged with electricity during the movement of the fixed section. Therefore, it is a useful invention that produces the effect of establishing an optimal OLEV operation system with a minimum investment cost.

Claims (20)

A target setting unit for setting the number of batteries to be used and the number of cable installation sections installed in the driving route;
An entity generation unit generating an entity set consisting of a predetermined number of entities;
A cost calculator for calculating an infrastructure construction cost for each entity;
A best object extracting unit for extracting a best object having a minimum value among infrastructure construction costs for all the objects constituting the population;
A self-optimal location extracting unit for extracting a self-optimal location that is a location representing the lowest infrastructure construction cost among the locations that have been moved, including the current location, for each entity;
A condition determination unit for outputting and terminating the best object when a termination condition is satisfied for the population;
A speed setting unit for setting an arbitrary moving speed for each individual object; And
Position moving unit for moving the position of the object according to the vector, the vector indicating the best object, the self-optimal position and the speed for each individual
Optimal infrastructure data extraction apparatus comprising a. The method of claim 1,
In the individual generation unit, the individual,
Optimal infrastructure data extraction apparatus, characterized in that the capacity of the battery, the cable installation section start point and end point set by setting the variable. 3. The method of claim 2,
In the individual generation unit, the individual,
Optimal infrastructure data extraction apparatus, characterized in that for setting the range of each variable to any value within the range. The method of claim 3,
Optimal infrastructure data extraction apparatus, characterized in that each variable of the object is set randomly within the range of valid values. The method of claim 1,
The apparatus for extracting optimal infrastructure data, characterized in that the moving speed for each individual is determined according to the difference between the position of the best object and the current point. The method of claim 1,
In the condition determination unit,
Optimal infrastructure data extraction apparatus, characterized in that terminates when the number of times to calculate the infrastructure construction cost is a predetermined number. 3. The method of claim 2,
In the individual generation unit,
Optimal infrastructure data extraction apparatus, characterized in that the position of the start point for each cable installation section is set to be smaller than the position of the end point. The method of claim 7, wherein
In the individual generation unit,
The object is optimal infrastructure data extraction device, characterized in that the setting between the position of the start point and the end point of any one cable installation section does not overlap with the other cable installation section. 9. The method of claim 8,
At the position indicating the first starting point, which is the starting point of the first cable installation section, the size of the first starting point is subtracted so that the magnitude of the battery's maximum chargeable power minus the power consumption to the first starting point is within a range larger than the recommended minimum charge amount of the battery. Optimal infrastructure data extraction apparatus, characterized in that for setting the location. 10. The method of claim 9,
The amount of power at the first end point, which is the end point of the first cable installation section, is the maximum charge possible as the sum of the amount of charge at the first cable installation section minus the power consumption to the first end point from the maximum chargeable power of the battery. Optimal infrastructure data extraction device, characterized in that not greater than the amount of power. The method of claim 10,
The starting point of the next cable installation section is set such that the amount of power consumed from the end point of one cable installation section minus the power consumption to the start point of the next cable installation section is within a range that is larger than the recommended minimum charge of the battery. Optimal infrastructure data extraction device. 12. The method of claim 11,
The amount of power available at the next end point, which is the end point of the next cable installation section, is the magnitude of the maximum chargeable power as the sum of the power consumption from the end point of the previous cable installation section to the next end point and the charging amount at the next cable installation section. Optimal infrastructure data extraction device, characterized in that not larger. The method of claim 12,
The amount of power at the end point of the running route is the amount of power consumed from the end point of the last cable installation section to the end point of the running route and is set to the end point of the last cable installation section to be larger than the recommended minimum charge amount. Optimal infrastructure data extraction apparatus characterized in that the. A target setting step of setting the number of batteries to be used and the number of cable installation sections installed in the driving route;
An entity generation step of generating an entity set consisting of a predetermined number of entities;
A cost calculation step of calculating an infrastructure construction cost for each individual;
A best object extracting step of extracting a best object having a minimum value among infrastructure construction costs for all the objects constituting the population;
A self-optimal location extraction step of extracting a self-optimal location that is a location representing the lowest infrastructure construction cost among the locations that have been moved, including the current location, for each individual;
A condition determination step of outputting and ending the best object when the termination condition is satisfied for the population;
A speed setting step of setting an arbitrary moving speed for each individual;
Position shifting step of moving the position of the object according to the vector to the best object, the vector representing the optimal position and the speed for each individual
Optimal infrastructure data extraction method comprising a. 15. The method of claim 14,
In the individual generation step, the individual,
Optimal infrastructure data extraction method characterized in that the capacity of the battery, the cable installation section start point and end point is set by setting the variable. 16. The method of claim 15,
In the individual generation step,
Optimal infrastructure data extraction method characterized in that the position of the starting point for each cable installation section is set to be smaller than the position of the end point. 17. The method of claim 16,
In the individual generation step,
The object is optimal infrastructure data extraction method, characterized in that set between the position of the start point and the end point of any one of the cable installation section does not overlap with the other cable installation section. 18. The method of claim 17,
The object indicating the start point of a cable installation section, the optimal infrastructure data extraction method, characterized in that the size of the subtraction of the power consumption up to the cable installation section before the start point is set to be larger than the recommended minimum charge of the battery. 19. The method of claim 18,
The amount of power at the end point of the running route is the amount of power consumed from the end point of the last cable installation section to the end point of the running route and is set to the end point of the last cable installation section to be larger than the recommended minimum charge amount. Optimal infrastructure data extraction method characterized in that. A computer-readable recording medium having recorded thereon a program for executing each step of the method for extracting optimal infrastructure data according to any one of claims 14 to 19.

Images